Radical Reads: Healthcare AI Enters the Mainstream

Investor Sanjana Basu shares her perspective on the areas where we expect to see AI generate outsized value including innovations in health data sets, genomics and precision medicine, generative AI applied to biology, and AI-enabled sleep solutions.

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Healthcare AI Enters the Mainstream

In Q1 2022, healthcare was the top-funded sector in AI, according to CB Insights’ global State of AI report and, against a backdrop of decreasing investment in healthcare, healthcare AI attracted $4.5B of funding in Q2 2022 and gained 3 new unicorns.

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Radical Reads: Am I a Founder?

What does it take to found a successful AI company? Radical Ventures Managing Partner and Co-Founder Jordan Jacobs explored this question with AI roboticist and multi-time founder Pieter Abbeel in the kick-off to this year’s AI Founders Master Class.

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AI Founders Master Class Poster with headshots of Fei-Fei Li, Pieter Abbeel, Richard Socher, Aidan Gomez, Raquel Urtasun, and Pieter Abbeel. Dates are provided: October 12, October 19, October 26, and November 2 starting at 5:00 pm ET.

Radical Reads: AI Founders Master Class

The AI Founders Master Class will be held virtually from October 12th to November 2rd, 2022 with speakers such as Fei-Fei Li, Co-Director of Stanford’s Human-Centered AI Institute, Pieter Abbeel, Co-Founder of Covariant and Director of the Berkeley Robot Learning Lab, Richard Socher, Co-Founder and CEO of, Raquel Urtasun, Founder and CEO of Waabi, and Aidan Gomez, Co-Founder and CEO of Cohere. 

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Aidan Gomez and Stephen Marche are seated on a stage at the Elevate Festival. Behind them are the words "AI Transform the Future: Elevate Festival"

Radical Reads: The Future of Language AI

Right now, we must learn the computer’s language. I went to school for five years to learn how to talk to a computer, to tell it what to do, and to code it. I learned to speak its language. We’re not yet in a place where our products speak our language. That will change…

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Objects generated by 3D-GAN from vectors, without a reference image/object. We show, for the last two objects in each row, the nearest neighbor retrieved from the training set. We see that the generated objects are similar, but not identical, to examples in the training set. For comparison, we show objects generated by the previous state-of-the-art [Wu et al., 2015] (results supplied by the authors). We also show objects generated by autoencoders trained on a single object category, with latent vectors sampled from empirical distribution. See paper Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling.

Radical Reads: Generative AI and the Evolution of Ideas

An idea, of course, is the domain of the human mind. Breakthrough advances in generative AI technology, however, are changing the notion of what it means to substantiate an idea, offering new mechanisms for creation and iteration that were – until just recently – entirely bound by our biological capacity…

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